Measurement error in imputation procedures

We study how estimators that are used to impute consumption in survey data are inconsistent due to measurement error in consumption. Previous research suggests instrumenting consumption to overcome this problem. We show that, if additional regressors are present, then instrumenting consumption may still produce inconsistent estimators due to the likely correlation between additional regressors and measurement error. On the other hand, low correlations between additional regressors and instruments may reduce bias due to measurement error. We apply our findings by revisiting recent research that imputes consumption data from the CEX to the PSID.     

Growth and Jobs in Developing Economies: Trends and Cycles

Open Economies Review - This paper investigates the relationship between economic growth and job creation in developing economies with a focus on low and lower middle-income countries along two...     

A common factor of stochastic volatilities between oil and commodity prices

This article analyses the multivariate stochastic volatilities (SVs) with a common factor influencing volatilities in the prices of crude oil and agricultural commodities, used for both biofuel and nonbiofuel purposes. Modelling the volatility is crucial because the volatility is an important variable for asset allocation, risk management and derivative pricing. We develop a SV model comprising a latent common volatility factor with two asymptotic regimes with a smooth transition between them. In contrast to conventional volatility models, SVs are generated by the logistic transformation of latent factors, which comprise two components: the common volatility factor and an idiosyncratic component. We present a SV model with a common factor for oil, corn and wheat from 8 August 2005 to 10 October 2014, using a Markov chain Monte Carlo method to estimate the SVs and extract the common volatility factor. We find that the volatilities of oil and grain markets are persistent. According to the estimated common volatility factor, high volatility periods match the 2007–2009 recession and the 2007–2008 financial crisis quite well. Finally, the extracted common volatility factor exhibits a distinct pattern.     

University Company Government Interaction： FAPEMIG as Propeller Agent of the Scientific-Technological Development in Minas Gerais, Brazil

This article aims to present the main indicators for Science, Technology, and Innovation （ST＆l） generated by the Fundacao de Amparo a Pesquisa do Estado de Minas Gerais （FAPEMIG） in four years （2008-2011）. The methodology used was a case study, with documentary research, held in the annual reports of activities of the foundation. The results showed that all indicators analyzed in aggregate form, evolved gradually. It is concluded that the FAPEMIG comes complying with their mission to induce and encourage research and scientific and technological innovation for the development of the State of Minas Gerais in the southeast region, maintaining the recognition as one of the main agents of development inductors ST＆I in Brazil.